Data for Berlin

import os,sys
sys.path.insert(0, os.path.normpath(os.path.join(os.path.abspath(''), '../../Code')))
from hedera_covid import DataHandlerBerlin, smooth_data

# for plotly
from plotly.offline import iplot
from plotly.offline import init_notebook_mode, plot
from IPython.core.display import display, HTML
import plotly as py
import plotly.tools as tls

import datetime
import numpy as np
import pandas as pd

# load data
berlin = DataHandlerBerlin()


# intensive care
berlin_h = pd.read_excel('../../DE-Data/intensive-care-data.xlsx',sheet_name = 'berlin')
germany_h = pd.read_excel('../../DE-Data/intensive-care-data.xlsx',sheet_name = 'germany')
bayern_h = pd.read_excel('../../DE-Data/intensive-care-data.xlsx',sheet_name = 'bayern')



    
    

import plotly.graph_objects as go
init_notebook_mode(connected=True)

fig = go.Figure()

N = len(berlin.data['dates'])

fig.add_trace(go.Bar(
    x=berlin.data['dates'],
    y=smooth_data(berlin.data['confirmed'],7),
    name='Reported Cases (Total = ' + str(berlin.data['confirmed'][N-1]) + ')'
))
fig.add_trace(go.Bar(
    x=berlin.data['dates'],
    y=smooth_data(berlin.data['deaths'],7),
    name='Reported Deaths (Total = ' + str(berlin.data['deaths'][N-1]) + ')'
))


fig.add_trace(go.Scatter(
    x=berlin.data['dates'],
    y=smooth_data(berlin.data['stationary'],7),
    name='In Hospital (Total = ' + str(berlin.data['stationary'][N-1]) + ')'
))

fig.add_trace(go.Scatter(
    x=berlin.data['dates'],
    y=smooth_data(berlin.data['intensive'],7),
    name='Intensive Care (Total = ' + str(berlin.data['intensive'][N-1]) + ')'
))
    
fig.update_layout(xaxis_tickangle=-90)

plot(fig, filename = 'figure.html')
display(HTML('figure.html'))

import plotly.graph_objects as go
init_notebook_mode(connected=True)

fig = go.Figure()


fig.add_trace(go.Bar(
    x=berlin.data['dates'],
    y=berlin.data['confirmed_daily'],
    name='Daily Reported Cases (Total = ' + str(berlin.data['confirmed'][N-1]) + ')',
    marker = {'color': "#117A65"}
))
n_smooth = 7
fig.add_trace(go.Scatter(
    x=berlin.data['dates'],
    y=smooth_data(berlin.data['confirmed_daily'],n=n_smooth),
    name='Averaged over ' + str(n_smooth) + ' days',
    marker = {'color': "#48C9B0"}
))

    
fig.update_layout(xaxis_tickangle=-90)
fig.update_layout(legend=dict(x=0.1, y=1.2),legend_orientation="h",font_size=10)

plot(fig, filename = 'figure.html')
display(HTML('figure.html'))

import plotly.graph_objects as go
init_notebook_mode(connected=True)

fig = go.Figure()



fig.add_trace(go.Bar(
    x=berlin.data['dates'],
    y=berlin.data['deaths_daily'],
    name='Daily Reported Deaths (Total = ' + str(berlin.data['deaths'][N-1]) + ')',
    marker = {'color':'#F7DC6F'}
))

n_smooth = 7
fig.add_trace(go.Scatter(
    x=berlin.data['dates'],
    y=smooth_data(berlin.data['deaths_daily'],n=n_smooth),
    name='Averaged over ' + str(n_smooth) + ' days',
    marker = {'color': "#EB984E"}
))
    
fig.update_layout(xaxis_tickangle=-90)
fig.update_layout(legend=dict(x=0.1, y=1.2),legend_orientation="h",font_size=10)

plot(fig, filename = 'figure.html')
display(HTML('figure.html'))

import plotly.graph_objects as go
init_notebook_mode(connected=True)

fig = go.Figure()


fig.add_trace(go.Bar(
    x=germany_h['Date'],
    y=germany_h['Percentage'],
    name='Germany',
    marker = {'color': "#F7DC6F"}
))
fig.add_trace(go.Bar(
    x=berlin_h['Date'],
    y=berlin_h['Percentage'],
    name='Berlin',
    marker = {'color': "#117A65"}
))
fig.add_trace(go.Bar(
    x=bayern_h['Date'],
    y=bayern_h['Percentage'],
    name='Bayern',
    marker = {'color': "#48C9B0"}
))


fig.update_layout(xaxis_tickangle=-90)
fig.update_layout(title='Percentage of intensive beds free',
                  font_size=10)

#fig.show()
plot(fig, filename = 'figure.html')
display(HTML('figure.html'))
g=10

from IPython.display import display, Markdown
N = len(germany_h['Reporting'])
g= germany_h['Reporting'][N-1]
d = germany_h['Date'][N-1]
display(Markdown(f'**Note** The graphics take into account only the reporting entities ({g} on {d})'))